Energy Efficient Hierarchical Clustering using HACOPSO in Wireless Sensor Networks

Abstract

The Wireless Sensor Network (WSN) is a collection of a various number of sensor node involved in a tremendous region for communicating data packets from one place to another in a productive way. The most significant techniques in the WSN are clustering, power consumption, lifetime and productive transmission of information in a secured manner with interconnected mobile nodes in networks. The clustering is the process of grouping the nodes for sharing the data packets to one cluster member to another cluster member through cluster heads present in the networks, which saves energy. Hence, K-Means clustering algorithm is used along with the Hybrid Ant Colony and Particle Swarm Optimization (HACOPSO) to produce a hierarchy of each CHs and observe that the energy savings increase with the number of levels present in the hierarchy. Ad hoc On-Demand Distance Vector Routing (AODV) uses two different operations to find and maintain routes: the route discovery process operation and route maintenance. Therefore, “K-Means-HACOPSO” methodology precisely transmit data from source to destination by evaluating better through-put, packet delivery ratio, packet loss, end-to-end delay and energy consumption in a secured environment.